View source: R/tidyMS_R6_Modelling.R
model_analyse | R Documentation |
used in project p2901
model_analyse(
pepIntensity,
model_strategy,
subject_Id = "protein_Id",
modelName = "Model"
)
Other modelling:
Contrasts
,
ContrastsMissing
,
ContrastsModerated
,
ContrastsPlotter
,
ContrastsProDA
,
ContrastsROPECA
,
ContrastsTable
,
INTERNAL_FUNCTIONS_BY_FAMILY
,
LR_test()
,
Model
,
build_model()
,
contrasts_fisher_exact()
,
get_anova_df()
,
get_complete_model_fit()
,
get_p_values_pbeta()
,
isSingular_lm()
,
linfct_all_possible_contrasts()
,
linfct_factors_contrasts()
,
linfct_from_model()
,
linfct_matrix_contrasts()
,
merge_contrasts_results()
,
model_summary()
,
moderated_p_limma()
,
moderated_p_limma_long()
,
my_contest()
,
my_contrast()
,
my_contrast_V1()
,
my_contrast_V2()
,
my_glht()
,
pivot_model_contrasts_2_Wide()
,
plot_lmer_peptide_predictions()
,
sim_build_models_lm()
,
sim_build_models_lmer()
,
sim_make_model_lm()
,
sim_make_model_lmer()
,
strategy_lmer()
,
summary_ROPECA_median_p.scaled()
x <- sim_lfq_data_peptide_config()
formula_randomPeptide <-
strategy_lmer("abundance ~ group_ + (1 | peptide_Id)")
mr <- model_analyse( x$data,
formula_randomPeptide,
subject_Id = x$config$table$hierarchy_keys_depth())
stopifnot(nrow(get_complete_model_fit(mr$modelProtein)) == 6)
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